Tool sprawl within organizations doesn’t just create a fragmented user experience; it poses a real threat to enterprises’ bottom lines.
Consider these statistics:
- 50% of organizations use multiple disparate tools to monitor resources, resulting in data silos, longer incident response times, and a fragmented user experience.
- Despite monitoring many IT systems and services, 47% of organizations cannot map all their on-premises, cloud, and edge devices to a single business view.
- According to Dell, organizations allocate 60 – 80% of their IT budgets to maintaining legacy systems.
This fragmentation significantly limits worker productivity. IT leaders spend hundreds of hours trying to manage multiple tools, map their environments, and upkeep aging systems that are either outdated or simply no longer necessary. They work tirelessly to manage increasingly complex IT estates and identify interdependencies between vastly different applications, but they still have limited visibility into how those tools are performing, whether they are working properly, or whether they can easily find the root causes of potential failures or system downtime.
Worse, a lack of complete visibility into the IT environment can lead to long-term cost implications. Organizations could end up wasting money on unused applications or overpaying for applications they do not need. They may be unable to effectively manage their cloud expenditures, directly impacting revenue and unnecessarily increasing operating costs.
That’s why, in 2025, IT administrators must resolve to consolidate and streamline their IT platforms by capturing comprehensive observability.
Moving beyond monitoring
Every IT administrator is familiar with network monitoring, but the traditional approach to monitoring is reactive—and no longer cutting it. Historically, an admin would receive an alert that something is amiss. They’d then check to see if it’s a real issue or a false alarm and, if necessary, attempt to fix the problem.
But observability takes the traditional approach to network monitoring a significant step further by proactively providing end-to-end visibility across the entire IT infrastructure. Observability outcomes which can be achieved with the ScienceLogic AI Platform through its automated root cause analysis capabilities uses a combination of AI and machine learning to analyze log events, detect anomalies, and deliver precise analysis insights and remediation recommendations.
IT managers no longer need to spend hours sifting through traces and logs. Instead, they get automated, real-time status updates, details on potential issues and their impacts on services, recommended actions to resolve incidents, and complete visibility into their entire IT operations.
Less manual effort means time and money saved on network monitoring and a reduced Mean Time to Repair (MTTR). Reducing the time spent monitoring allows developers and IT managers to focus their resources on value-adding tasks like developing applications that drive better business outcomes. Shorter MTTR helps minimize IT downtime, which can cost some organizations $9,000 per minute.
Minimizing tool sprawl
Despite an abundance of monitoring tools and associated costs, a report from Dell and highlighted in our recent ebook found that 47% of organizations are still unable to map all their on-premises, cloud, and edge devices into a single view.
Observability can help companies gain a complete view of every asset in their IT environments by providing administrators with a powerful means of identifying outdated or non-performing legacy applications and tools that might cost their organizations millions of dollars in operating costs.
With enhanced visibility, administrators can identify application redundancies, which lead to inefficiencies as organizations incur unnecessary licensing fees, maintenance costs, and resource allocation for multiple tools that perform similar functions. By detecting and eliminating these redundancies through observability, organizations can optimize both costs and operational efficiency.
Laying the groundwork for automation
Ultimately, observability lays the critical foundation for autonomous IT operations—an approach we call Autonomic IT. In this state, IT systems are self-managing, self-healing, and self-optimizing – introducing new levels of efficiency. These self-healing systems can successfully resolve incidents without the need for human intervention.
With Autonomic IT, administrators don’t have to worry about manually managing or configuring vastly complex hybrid IT environments. The system automatically does this by employing AI, machine learning, and automation to detect, predict, prevent, and respond to incidents – without the need for human intervention. Administrators are pulled into the loop only as necessary. Otherwise, they can focus on delivering innovative products and services and continue positively impacting their organizations’ balance sheets.
Contact us today to start leveraging the ScienceLogic AI Platform and Skylar AI’s suite of advanced AI capabilities to capture comprehensive observability and transform your IT operations.
